Implanted Battery-Free Direct-Current Micro-Power Supply from in Vivo Breath Energy Harvesting

Computational modeling, instrumented linkages, optical technologies, MRI, and radiographic techniques have been widely used to study knee motion after total knee replacement (TKR) surgery. Information provided by these methods has helped designers to develop implants with better clinical performance and surgeons to obtain an improved understanding of the stability and mobility of the joint. Correspondingly, overall patient satisfaction with respect to the reduction in pain and recovery of normal functioning of the joint has been improving. However, about 20% of patients are still not fully satisfied with their surgical outcomes. The main obstacle in the current state-of-the-art is that a comprehensive post-operative understanding of knee balance is still unavailable, mostly due to a lack of in vivo data collected from the joint after surgery. This work presents an attempt to develop a self-powered instrumented knee implant for in vivo data acquisition. The knee sensory system in this study utilizes several embedded piezoelectric transducers in the tibial bearing of the knee replacement in order to provide sensing and energy harvesting capabilities. Through a series of analytical modeling, finite element simulation, and experimental testing, the performance of the suggested system is evaluated and a dimensionally optimized design of an instrumented TKR is achieved. More specifically, a comprehensive platform is established in order to combine the knowledge of embedded piezoelectric sensors and energy harvesters, musculoskeletal modeling of the knee joint, multiphysics finite element modeling, additive manufacturing techniques, image processing, and experimental knee loading simulation in order to achieve the experimentally validated and optimized instrumented knee implant design. The cumulative work presented in this article encompasses three main studies performed on the sensing performance of the proposed design: first, preliminary parametric studies of the effect of local dimensional and material parameters on the electromechanical behavior of the embedded sensory system; second, investigation of the ability to sense total force and center of pressure location; and third, evaluation of an enhanced system with the ability to sense compartmental forces and contact locations. Additionally, the energy harvesting capacity of the system is investigated to ensure the achievement of a fully self-powered sensory system. Results obtained from the experimental analysis of the system demonstrate the successful sensing and energy harvesting performance of the designs achieved in this study.

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Theory of energy harvesting from heartbeat including the effects of pleural cavity and respiration

Proceedings of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rspa.2017.0615 ◽

2017 ◽

Vol 473 (2207) ◽

pp. 20170615 ◽

Cited By ~ 1

Author(s):

Yangyang Zhang ◽

Bingwei Lu ◽

Chaofeng Lü ◽

Xue Feng

Keyword(s):

Energy Harvesting ◽

Pleural Cavity ◽

Scaling Law ◽

Battery Life ◽

Deformation Model ◽

Experimental Measurements ◽

Combined System ◽

Energy Harvesters ◽

Piezoelectric Energy

Self-powered implantable devices with flexible energy harvesters are of significant interest due to their potential to solve the problem of limited battery life and surgical replacement. The flexible electronic devices made of piezoelectric materials have been employed to harvest energy from the motion of biological organs. Experimental measurements show that the output voltage of the device mounted on porcine left ventricle in chest closed environment decreases significantly compared to the case of chest open. A restricted-space deformation model is proposed to predict the impeding effect of pleural cavity, surrounding tissues, as well as respiration on the efficiency of energy harvesting from heartbeat using flexible piezoelectric devices. The analytical solution is verified by comparing theoretical predictions to experimental measurements. A simple scaling law is established to analyse the intrinsic correlations between the normalized output power and the combined system parameters, i.e. the normalized permitted space and normalized electrical load. The results may provide guidelines for optimization of in vivo energy harvesting from heartbeat or the motions of other biological organs using flexible piezoelectric energy harvesters.

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